Two Conserved Cysteine Triads in Human Ero1α Cooperate for Efficient Disulfide Bond Formation in the Endoplasmic Reticulum

Human Ero1alpha is an endoplasmic reticulum (ER)-resident protein responsible for protein disulfide isomerase (PDI) oxidation. To clarify the molecular mechanisms underlying its function, we generated a panel of cysteine replacement mutants and analyzed their capability of: 1) complementing a temperature-sensitive yeast Ero1 mutant, 2) favoring oxidative folding in mammalian cells, 3) forming mixed disulfides with PDI and ERp44, and 4) adopting characteristic redox-dependent conformations. Our results reveal that two essential cysteine triads (Cys85-Cys94-Cys99 and Cys391-Cys394-Cys397) cooperate in electron transfer, with Cys94 likely forming mixed disulfides with PDI. Dominant negative phenotypes arise when critical residues within the triads are mutated (Cys394, Cys397, and to a lesser extent Cys99). Replacing the first cysteine in either triad (Cys85 or Cys391) generates mutants with weaker activity. In addition, mutating either Cys85 or Cys391, but not Cys397, reverts the dominant negative phenotype of the C394A mutant. These findings suggest that interactions between the two triads, dependent on Cys85 and Cys391, are important for Ero1alpha function, possibly stabilizing a platform for efficient PDI oxidation

The C-terminal domain of yeast Ero1p mediates membrane localization and is essential for function

AbstractIn eukaryotes, members of the Ero1 family control oxidative protein folding in the endoplasmic reticulum (ER). Yeast Ero1p is tightly associated with the ER membrane, despite cleavage of the leader peptide, the only hydrophobic sequence that could mediate lipid insertion. In contrast, human Ero1-Lα and a yeast mutant (Ero1pΔC) lacking the 127 C-terminal amino acids are soluble when expressed in yeast. Neither Ero1-Lα nor Ero1pΔC complements an ERO1 disrupted strain. Appending the yeast C-terminal tail to human Ero1-Lα restores membrane association and allows growth of ERO1 disrupted cells. Therefore, the tail of Ero1p mediates membrane association and is crucial for function

DECLINE OF PREVALENCE OF RESISTANCE ASSOCIATED SUBSTITUTIONS TO NS3 AND NS5A INHIBITORS AT DAA- FAILURE IN HEPATITIS C VIRUS IN ITALY OVER THE YEARS 2015 TO 2018

Background: A minority of patients fails to eliminate HCV and resistance-associated substitutions (RASs) are commonly detected at failure of interferon-free DAA regimens . Methods: Within the Italian network VIRONET-C, the prevalence of NS3/NS5A/NS5B RASs was retrospectively evaluated in patients who failed an EASL recommended DAA-regimen in 2015-2018 . The geno2pheno system and Sorbo MC et al. Drug Resistance Updates 2018 were used to infer HCV- genotype/subtype and predict drug resistance . The changes in prevalence of RASs over time were evaluated by chi-square test for trend, predictors of RASs at failure were analysed by logistic regression . Results: We included 386 HCV infected patients: 75% males, median age was 56 years (IQR 52-61), metavir fibrosis stage F4 in 76%; 106 (28%) were treatment- experienced: 91 (86%) with IFN-based treatments, 26 (25%) with DAAs. Patients with HIV and HBV coinfection were 10% (33/317) and 8% (6/72), respectively. HCV genotype was 1b in 122 pts (32%), 3 in 109 (28%), 1a in 97 (25%), 4 in 37 (10%), 2 in 21 (5%). DAA regimens were: LDV/SOF in 115 (30%), DCV/SOF in 103 (27%), 3D in 83 (21%), EBR/GRZ in 32 (8%), VEL/SOF in 29 (7%), GLE/PIB in 18 (5%) and 2D in 6 (2%); ribavirin was administered in 123 (32%) . The NS5A fasta-sequence was available for all patients, NS5B for 361 (94%), NS3 for 365 (95%) . According to the DAA failed the prevalence of any RASs was 90%, namely 80/135 (59%) in NS3, 313/359 (87%) in NS5A, 114/286 (40%) in NS5B . The prevalence of any RASs significantly declined from 2015 to 2018 (93% vs 70%, p=0.004): NS5A RASs from 90% to 72% (p=0 .29), NS3 RASs from 74% to 18% (p<0 .001), while NS5B RASs remained stable . Independent predictors of any RASs included advanced fibrosis (AOR 6.1, CI 95% 1.8-20.3, p=0 .004) and genotype (G2 vs G1a AOR 0 .03, CI 95% 0 .002- 0 .31, p=0 .004; G3 vs G1a AOR 0 .08, CI 95% 0 .01-0 .62, p=0 .02; G4 vs G1a AOR 0 .05, CI 95% 0 .006-0 .46, p=0 .008), after adjusting for age, previous HCV treatment and year of genotype . Notably, full activity was predicted for GLE/PIB in 75% of cases and for at least two components of VEL/SOF/VOX in 53% of cases, no case with full-resistance to either regimen was found . Conclusion: Despite decreasing prevalence over the years, RASs remain common at virological failure of DAA treatment, particularly in patients with the highest grade of liver fibrosis. The identification of RASs after failure could play a crucial role in optimizing retreatment strategies

MicroRNAs as Biomarkers for Diagnosis, Prognosis and Theranostics in Prostate Cancer

Prostate cancer (PC) includes several phenotypes, from indolent to highly aggressive cancer. Actual diagnostic and prognostic tools have several limitations, and there is a need for new biomarkers to stratify patients and assign them optimal therapies by taking into account potential genetic and epigenetic differences. MicroRNAs (miRNAs) are small sequences of non-coding RNA regulating specific genes involved in the onset and development of PC. Stable miRNAs have been found in biofluids, such as serum and plasma; thus, the measurement of PC-associated miRNAs is emerging as a non-invasive tool for PC detection and monitoring. In this study, we conduct an in-depth literature review focusing on miRNAs that may contribute to the diagnosis and prognosis of PC. The role of miRNAs as a potential theranostic tool in PC is discussed. Using a meta-analysis approach, we found a group of 29 miRNAs with diagnostic properties and a group of seven miRNAs with prognostic properties, which were found already expressed in both biofluids and PC tissues. We tested the two miRNA groups on The Cancer Genome Atlas dataset of PC tissue samples with a machine-learning approach. Our results suggest that these 29 miRNAs should be considered as potential panel of biomarkers for the diagnosis of PC, both as in vivo non-invasive test and ex vivo confirmation test

In silico identification of drug target pathways in breast cancer subtypes using pathway cross-talk inhibition

Abstract Background Despite great development in genome and proteome high-throughput methods, treatment failure is a critical point in the management of most solid cancers, including breast cancer (BC). Multiple alternative mechanisms upon drug treatment are involved to offset therapeutic effects, eventually causing drug resistance or treatment failure. Methods Here, we optimized a computational method to discover novel drug target pathways in cancer subtypes using pathway cross-talk inhibition (PCI). The in silico method is based on the detection and quantification of the pathway cross-talk for distinct cancer subtypes. From a BC data set of The Cancer Genome Atlas, we have identified different networks of cross-talking pathways for different BC subtypes, validated using an independent BC dataset from Gene Expression Omnibus. Then, we predicted in silico the effects of new or approved drugs on different BC subtypes by silencing individual or combined subtype-derived pathways with the aim to find new potential drugs or more effective synergistic combinations of drugs. Results Overall, we identified a set of new potential drug target pathways for distinct BC subtypes on which therapeutic agents could synergically act showing antitumour effects and impacting on cross-talk inhibition. Conclusions We believe that in silico methods based on PCI could offer valuable approaches to identifying more tailored and effective treatments in particular in heterogeneous cancer diseases

In Silico Discovery of Candidate Drugs against Covid-19

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide

Radiogenomics, Breast Cancer Diagnosis and Characterization: Current Status and Future Directions

Breast cancer (BC) is a heterogeneous disease, affecting millions of women every year. Early diagnosis is crucial to increasing survival. The clinical workup of BC diagnosis involves diagnostic imaging and bioptic characterization. In recent years, technical advances in image processing allowed for the application of advanced image analysis (radiomics) to clinical data. Furthermore, -omics technologies showed their potential in the characterization of BC. Combining information provided by radiomics with –omics data can be important to personalize diagnostic and therapeutic work up in a clinical context for the benefit of the patient. In this review, we analyzed the recent literature, highlighting innovative approaches to combine imaging and biochemical/biological data, with the aim of identifying recent advances in radiogenomics applied to BC. The results of radiogenomic studies are encouraging approaches in a clinical setting. Despite this, as radiogenomics is an emerging area, the optimal approach has to face technical limitations and needs to be applied to large cohorts including all the expression profiles currently available for BC subtypes (e.g., besides markers from transcriptomics, proteomics and miRNomics, also other non-coding RNA profiles)